Falls affect millions of people each year and result in significant injuries, particularly among the elderly. In fact, it has been estimated that falls are one of the top three causes of death in elderly people. A fall can be defined as a sudden, uncontrolled and unintentional downward displacement of the body to the ground followed by an impact.
Personal Help Buttons (PHBs) are available that require the user to push the button to summon help in an emergency. However, if the user suffers a severe fall (for example if they are knocked unconscious), the user might be unable to push the button, which might mean that help doesn't arrive for a significant period of time, particularly if the user lives alone.
Fall detectors are also available that process the output of one or more movement sensors to determine if the user has suffered a fall. However, it has been found that these fall detectors have an unfavourable trade-off between fall detection probability and false alarm rate.
Given that a high false alarm rate will result in additional costs to the organisation responsible for giving assistance to the user of the fall detector (i.e. they will need to contact or visit the user of the fall detector when the fall detection alarm is triggered) and that a high false alarm rate is undesirable for the user of the fall detector, it has been found that an economically viable fall detector should provide a false alarm rate of, say, less than one false alarm in each two-month period, while maintaining a (positive) fall detection probability above 95 percent.
Most existing body-worn fall detectors make use of an accelerometer (usually a 3D accelerometer that measures acceleration in three dimensions) and they try to infer the occurrence of a fall by processing the time series generated by the accelerometer. Some fall detectors can also include an air pressure sensor, for example as described in WO 2004/114245. However, these existing fall detectors do not meet the detection requirements set out above.
Thus, one of the main disadvantages of existing fall detectors is their moderate reliability as expressed by a Receiver Operating Curve (ROC). The ROC expresses the achievable probability of detecting a fall versus the false alarm probability for different settings of parameters of a given system.
Even with an extended set of features (i.e. determining more than just an impact from the accelerometer measurements and a change in height from the pressure sensor measurements), it has been found that it is difficult to obtain a satisfactory performance if each feature is simply compared to a threshold and the subsequent reasoning only involves the feature-wise binary outcomes of these comparisons.
Therefore, there is a need for an improved method for detecting falls.